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Body Fluids

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Predictors of mid-term functional outcomes for robot-assisted Madigan simple prostatectomy: results of a multicentric series according to the BPH-6 achievement.

Minerva urology and nephrology
BACKGROUND: BPH-6 achievement remains an objective far to be evaluated for every technique currently available for the surgical management of bladder outlet obstruction (BOO) with the goal of preserving ejaculatory function. The aim of this study was...

A Novel Prediction Method of Transfer-Assisted Action Oriented to Individual Differences for the Excretion Care Robot.

Sensors (Basel, Switzerland)
The excretion care robot's (ECR) accurate recognition of transfer-assisted actions is crucial during its usage. However, transfer action recognition is a challenging task, especially since the differentiation of actions seriously affects its recognit...

Exhaled breath signal analysis for diabetes detection: an optimized deep learning approach.

Computer methods in biomechanics and biomedical engineering
In this study, a flexible deep learning system for breath analysis is created using an optimal hybrid deep learning model. To improve the quality of the gathered breath signals, the raw data are first pre-processed. Then, the most relevant features l...

Applications of Artificial Intelligence in Urinalysis: Is the Future Already Here?

Clinical chemistry
BACKGROUND: Artificial intelligence (AI) has emerged as a promising and transformative tool in the field of urinalysis, offering substantial potential for advancements in disease diagnosis and the development of predictive models for monitoring medic...

Comparison of Sysmex XN-V body fluid mode and deep-learning-based quantification with manual techniques for total nucleated cell count and differential count for equine bronchoalveolar lavage samples.

BMC veterinary research
BACKGROUND: Bronchoalveolar lavage (BAL) is a diagnostic method for the assessment of the lower respiratory airway health status in horses. Differential cell count and sometimes also total nucleated cell count (TNCC) are routinely measured by time-co...

Developing an interpretation model for body fluid identification.

Forensic science international
Criminal investigations, particularly sexual assaults, frequently require the identification of body fluid type in addition to body fluid donor to provide context. In most cases this can be achieved by conventional methods, however, in certain scenar...

A multi-class support vector machine classification model based on 14 microRNAs for forensic body fluid identification.

Forensic science international. Genetics
MicroRNAs (miRNAs) are promising biomarkers for forensic body fluid identification owing to their small size, stability against degradation, and differential expression patterns. However, the expression of most body fluid-miRNAs is relative (differen...

Bacterial profile-based body fluid identification using a machine learning approach.

Genes & genomics
BACKGROUND: Identifying the origins of biological traces is critical for the reconstruction of crime scenes in forensic investigations. Traditional methods for body fluid identification rely on chemical, enzymatic, immunological, and spectroscopic te...

Rapid diagnosis of bacterial vaginosis using machine-learning-assisted surface-enhanced Raman spectroscopy of human vaginal fluids.

mSystems
UNLABELLED: Bacterial vaginosis (BV) is an abnormal gynecological condition caused by the overgrowth of specific bacteria in the vagina. This study aims to develop a novel method for BV detection by integrating surface-enhanced Raman scattering (SERS...

Vibrational spectroscopy of body fluids combined with machine learning for the early diagnosis of cystic echinococcosis.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Cystic echinococcosis (CE) is a globally prevalent zoonotic parasitic disease. Due to the covert symptoms and the inadequacies of screening technologies, accurate early diagnosis is crucial. This study explores the feasibility of employing body fluid...